Production scheduling with sequence-dependent setups and job release times

This paper studies a shortterm production scheduling problem inspired from reallife manufacturing systems consisting on the scheduling a set of jobs (production orders) on both a single machine and identical parallel machines with the objective of minimizing the makespan or maximum completion time of all jobs. Jobs are subject to release dates and there are sequence-dependent machine setup times. Since this problem is known to be strongly NP-hard even for the single machine case, this paper proposes a heuristic algorithm to solve it. The algorithm uses a strategy of random generation of various execution sequences, and then selects the best of such schedules. Experiments are performed using random-generated data and show that the heuristic performs very well compared against the optimal solution and lower bounds, and requiring short computational time